Advances for Artificial Intelligence in Health Data Analytics to Drive Digital Systems Innovation

Digital Systems Innovation For Health Data Analytics Adopting Aih

Researchers have long argued that the adoption rate of Electronic Health Record (EHR) systems is an important indicator of the degree of national e-health (Bonomi 2016). More recently adavnces have been made adopting AIH to d-health systems. This is also a measurement in the success of creating, sharing, distribution, of data analytics. Health Data is essential for digital innovation systems to function. Hambleton and Aloizos (2019) argue that the healthcare industry is one of the last industries to be disrupted by digital technologies especially focusing on AIH. It arguably has the most to gain, particularly from timely, accurate communication and clinical improvements, especially medication safety adopting AIH. At a time when governments of different countries willing to provide quality healthcare to their citizens on a digital platform, AIH can provide innovative solutions to severe healthcare problems. For example: Singapore government have made digital health a top priority for their citizens (RIE2020). Jha et al. (2008) state that health information technology in general and EHRs in particular, are tools for improving the quality, safety and efficiency of health systems in countries. They observed that in UK, Netherlands, Australia, and New Zealand generally used EHRs among general practitioners (each country>90%); Germany was far behind (40–80%); and there was a small minority of doctors in the U.S. and Canada who used EHRs (10–30%). They also explained that it is difficult for hospitals to obtain quality data and that only a small fraction of hospitals (<10%), of the countries analyzed had the key components required by an EHR. As shown in Table 1 digital systems have many benefits over paper-based systems.